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NSGA-II and MOPSO based optimization for sizing of hybrid PV / wind / battery energy storage system

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dc.citedby44
dc.contributor.authorMohamad Izdin Hlal A.en_US
dc.contributor.authorRamachandaramurthya V.K.en_US
dc.contributor.authorSanjeevikumar Padmanaban B.en_US
dc.contributor.authorHamid Reza Kaboli C.en_US
dc.contributor.authorAref Pouryekta A.en_US
dc.contributor.authorTuan Ab Rashid Bin Tuan Abdullah D.en_US
dc.contributor.authorid57205344223en_US
dc.contributor.authorid57205340564en_US
dc.contributor.authorid57205339630en_US
dc.contributor.authorid57205345268en_US
dc.contributor.authorid57205337048en_US
dc.contributor.authorid57205338636en_US
dc.date.accessioned2023-05-29T07:26:47Z
dc.date.available2023-05-29T07:26:47Z
dc.date.issued2019
dc.description.abstractThis paper presents a Stand-alone Hybrid Renewable Energy System (SHRES) as an alternative to fossil fuel based generators. The Photovoltaic (PV) panels and wind turbines (WT) are designed for the Malaysian low wind speed conditions with battery Energy Storage (BES) to provide electric power to the load. The appropriate sizing of each component was accomplished using Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO) techniques. The optimized hybrid system was examined in MATLAB using two case studies to find the optimum number of PV panels, wind turbines system and BES that minimizes the Loss of Power Supply Probability (LPSP) and Cost of Energy (COE). The hybrid power system was connected to the AC bus to investigate the system performance in supplying a rural settlement. Real weather data at the location of interest was utilized in this paper. The results obtained from the two scenarios were used to compare the suitability of the NSGA-II and MOPSO methods. The NSGA-II method is shown to be more accurate whereas the MOPSO method is faster in executing the optimization. Hence, both these methods can be used for techno-economic optimization of SHRES. � 2019 Institute of Advanced Engineering and Science. All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.11591/ijpeds.v10.i1.pp463-478
dc.identifier.epage478
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85059626055
dc.identifier.spage463
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85059626055&doi=10.11591%2fijpeds.v10.i1.pp463-478&partnerID=40&md5=1c5d6004f923c7fc758cf0aa07b49792
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24762
dc.identifier.volume10
dc.publisherInstitute of Advanced Engineering and Scienceen_US
dc.relation.ispartofAll Open Access, Gold, Green
dc.sourceScopus
dc.sourcetitleInternational Journal of Power Electronics and Drive Systems
dc.titleNSGA-II and MOPSO based optimization for sizing of hybrid PV / wind / battery energy storage systemen_US
dc.typeArticleen_US
dspace.entity.typePublication
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